Modern Neural Networks Remain Interpretable at Trillion-Parameter Scale, Goodfire Researcher Reports
Goodfire researcher Nick Cammarata reports that modern neural networks are far more interpretable than widely assumed, with most neurons remaining understandable in models scaling up to trillions of parameters.
